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It’s truly wild that we’re getting this level of performance from open models. Congrats to Kimi team on this. Every time we lower the cost of frontier intelligence, the use-cases that enterprises can take on just go up. There’s a tremendous amount of workflows that enterprises would love to deploy that are only gated by the cost of tokens. Importantly for the startup ecosystem, the combined breakthroughs from open and closed labs enable a ton of value to accrue to the layer, which can leverage a variety of models to complete full tasks for customers. This diversity of models and approaches means that the applied AI layer can tune models to their workflows and route intelligence appropriately. Huge win for all.
Introducing Kimi K3: Open Frontier Intelligence 🔹 2.8 Trillion Parameters, 1 Million Context, Native Multimodal 🔹 Kimi Delta Attention enables up to 6.3x faster decoding in million-token contexts 🔹 Attention Residuals deliver ~25% higher training efficiency at <2% additional cost 🔹 Built for long-horizon agentic coding and self-evolving workflows Kimi K3 is now live on on http://Kimi.com, Kimi Work, Kimi Code, and the Kimi API. Open Weights by July 27, 2026. 🔗 API: http://platform.kimi.ai 🔗 Tech blog: http://kimi.com/blog/kimi-k3
It’s imperative that we continue to have a cycle of frontier breakthroughs that push the limits of what AI can do, and then a fast follow of cheaper or tuned AI on proven tasks and use-cases. This flywheel allows for an incredible amount of value to be generated across the AI ecosystem, and is the thing that enables broad scale adoption across the economy. Kimi k3 is another great entry into that cycle. And this whole past week has shown what this cycle can look like across OpenAI, Meta, SpaceX, Thinking Machines, Kimi, and more. Excited for this to continue.